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# -*- coding: utf-8 -*-
"""
Created on Sat Apr 23 20:23:23 2022
@author: kbpat
"""
import pandas as pd
import streamlit as st
df1= pd.read_excel("INDIA INFLATION RATE.xlsx",names=('Year','IR','AC'),parse_dates=[0])
from statsmodels.tsa.stattools import adfuller
def adf_test(dataset):
dftest = adfuller(dataset, autolag = 'AIC')
print("1. ADF : ",dftest[0])
print("2. P-Value : ", dftest[1])
print("3. Num Of Lags : ", dftest[2])
print("4. Num Of Observations Used For ADF Regression and Critical Values Calculation :", dftest[3])
print("5. Critical Values :")
for key, val in dftest[4].items():
print("\t",key, ": ", val)
adf_test(df1['IR'])
from pmdarima import auto_arima
import warnings
warnings.filterwarnings("ignore")
stepwise_fit = auto_arima(df1['IR'], trace=True,
suppress_warnings=True)
stepwise_fit.summary()
prediction=stepwise_fit.predict()
print(prediction)
def main():
st.title("Model Deployment:Inflation Rate")
html_temp = """
<div style="background-color:tomato;padding:10px">
<h2 style="color:white;text-align:center;"> INFLATION RATE </h2>
</div>
"""
st.markdown(html_temp,unsafe_allow_html=True)
Inflation = st.text_input("Inflation","Type Here")
Year = st.text_input("Year","Type Here")
result=""
if st.button("Predict"):
result=prediction
st.success('The output is {}'.format(result))
if st.button("About"):
st.text("https://www.macrotrends.net/countries/IND/india/inflation-rate-cpi")
st.text("Built with Streamlit")
if __name__=='__main__':
main()
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